def _adjust_date(self, date):
date = (date + BDay(1) - BDay(1)).date() # 1st move to latest weekday.
if self.calendars == 'Weekend' or is_business_day(
date, self.calendars):
return date
else:
return prev_business_date(date, self.calendars)
def _schedule_first_reports(self,
position_dates: List[dt.date],
show_progress: bool = True):
dates_before_today = list(
filter(lambda x: x < dt.date.today(), position_dates))
latest_date_before_today = max(dates_before_today)
self._schedule_reports(start_date=min(position_dates),
end_date=max(latest_date_before_today,
prev_business_date()))
if dt.date.today() in position_dates:
self._schedule_reports(start_date=latest_date_before_today,
end_date=dt.date.today())
if show_progress:
self._show_report_progress()
def set_start_date(self, start: dt.date):
self.performance[prev_business_date(start)] = 100
def set_start_date(self, start: dt.date):
self.performance[prev_business_date(start)] = self.initial_value
self.holdings[self.cash_asset] = self.initial_value
def calc(self,
risk_measure: Union[RiskMeasure, Iterable[RiskMeasure]],
fn=None) -> PortfolioRiskResult:
# PortfolioRiskResult should hold a copy of the portfolio instead of a reference to the portfolio
# this is to prevent the portfolio object within portfolioriskresult to hold a reference to the portfolio
# object should it later be modified in place (eg: resolution)
# If a position set portfolio, resolve positions held on each date in pricing context
if self.priceables:
with self.__pricing_context:
return PortfolioRiskResult(
copy.deepcopy(self), (risk_measure, ) if isinstance(
risk_measure, RiskMeasure) else risk_measure,
[p.calc(risk_measure, fn=fn) for p in self.__priceables])
if self.id or self.position_sets:
priceables_map = self.convert_positions_to_priceables()
list_of_risk_measures = (risk_measure, ) if isinstance(
risk_measure, RiskMeasure) else risk_measure
risk_pricing_context = list_of_risk_measures[0].pricing_context
# If the pricing context is historical, calc based on position sets held on each date
if isinstance(risk_pricing_context, HistoricalPricingContext):
date_range = risk_pricing_context._HistoricalPricingContext__date_range
start_date = min(date_range)
end_date = max(date_range)
position_dates = priceables_map.keys()
futures = []
while start_date <= end_date:
position_dates_after_start = sorted(
list(
filter(lambda date: start_date < date,
position_dates)))
context_end = min(position_dates_after_start[0], end_date) \
if position_dates_after_start else end_date
if context_end != end_date:
context_end = context_end - dt.timedelta(days=1)
historical_pricing_context = HistoricalPricingContext(
start=start_date,
end=prev_business_date(context_end)
if context_end != end_date else end_date)
with historical_pricing_context:
futures = futures + [
p.calc(risk_measure, fn=fn)
for p in self._get_priceables_from_map(
priceables_map, start_date)
]
start_date = context_end + dt.timedelta(days=1)
with self.__pricing_context:
return PortfolioRiskResult(
copy.deepcopy(self), (risk_measure, ) if isinstance(
risk_measure, RiskMeasure) else risk_measure,
futures)
# If the pricing context exists, calc based on the position set held on the pricing date
elif isinstance(risk_pricing_context, PricingContext):
futures = [
p.calc(risk_measure, fn=fn)
for p in self._get_priceables_from_map(
priceables_map, risk_pricing_context.pricing_date)
]
with self.__pricing_context:
return PortfolioRiskResult(
copy.deepcopy(self), (risk_measure, ) if isinstance(
risk_measure, RiskMeasure) else risk_measure,
futures)
return None
def set_start_date(self, start: dt.date):
self.performance[prev_business_date(start)] = 100
self.holdings[self.cash_asset] = 100
self.holdings_projected[self.cash_asset] = 100
def _adjust_date(self, date):
if is_business_day(date, self.calendars):
return date
else:
return prev_business_date(date, self.calendars)